5 Commits (main)

Author	SHA1	Message	Date
Ashwanth	11b1dcb2a3	chore(engine): introduce execution capture (#19821)	1 month ago
renovate-sh-app[bot]	d76b3bf495	fix(deps): update module github.com/apache/arrow-go/v18 to v18.4.1 (main) (#19750) ... Signed-off-by: renovate-sh-app[bot] <219655108+renovate-sh-app[bot]@users.noreply.github.com> Co-authored-by: renovate-sh-app[bot] <219655108+renovate-sh-app[bot]@users.noreply.github.com> Co-authored-by: Paul Rogers <paul.rogers@grafana.com>	2 months ago
Robert Fratto	cfd07c3683	chore(engine): simplify Pipeline interface (#19518)	2 months ago
Christian Haudum	8b7ef09e69	chore(engine): Cleanup: remove state from pipelines (#19495) ... * Do not pass `state` in `genericPipeline` but instead return `(arrow.Record, error)` in `readFunc` * Remove unused `state` fields from pipelines.	2 months ago
Robert Fratto	2e418b13fd	chore(engine): unexport subpackages (#19384) ... This moves packages around to reduce the surface area of the public engine API: * `pkg/engine/planner` moves to `pkg/engine/internal/planner` * `pkg/engine/executor` moves to `pkg/engine/internal/executor` These packages were only used from `pkg/engine` and did not need to be public. We may make them public again in the future if we want to expose subcomponents of the engine. This move means that `pkg/engine/planner/internal/tree` became `pkg/engine/internal/planner/internal/tree`. To reduce the import path, I also moved that package to `pkg/engine/internal/util/tree`. Other than moving files and updating import paths, no code changes are made. Signed-off-by: Robert Fratto <robertfratto@gmail.com>	3 months ago
Christian Haudum	65de5f95db	chore(engine): Simplify `Pipeline` interface (#19110) ... This PR replaces the two calls to retrieve a value from the pipeline with a single one. To do this, the `Read()` method now returns two arguments: `arrow.Record` and `error`, rather than just the error. If the error is not `nil`, the first argument (arrow.Record) must be ignored by the caller. The `Value()` method is not needed any more and was removed. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	4 months ago
Christian Haudum	cea56469b9	chore(engine): Pass context to Pipeline's Read() function (#18459) ... This change unifies how the request context is passed through the execution of pipelines. Instead of storing the context on pipelines, pass them as argument to the `Read()` function. This change alters the interface method of `Pipeline` from `Read() bool` to `Read(context.Context) bool`. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	6 months ago
Christian Haudum	b316d52612	chore(engine): Use shard information from query frontend in the new query engine (#17792) ... **What this PR does / why we need it**: This PR introduces the sharding to the new query engine to be able to test the engine using the exsiting Loki architecture with query frontend, query scheduler, and queriers. **Note, this is only an interim solution used for validating and testing.** By design, the first phase of the query engine implementation does only local execution of queries without sharding or time-based splitting. However, for testing the results of this first phase, we can utilise dual-ingestion (writing both chunks/tsdb and data objects in a way that sharding and splitting is performed in the query frontend using the existing middlewares. On the queriers themselves, the sub-queries are parsed and planned using the new logical and physical planner. If the query can successfully be planned, it will be executed by the new engine, otherwise it falls back to the old engine. **Shard size considerations** While performing time-splitting in the frontend works for data objects as well, sharding by information from TSDB is not directly mappable to data objects. The default target shard size in TSDB is 600MB (decompressed), whereas target size of data objects is 1GB compressed or roughly 10-15GB uncompressed. However, individual logs sections of a data object have a target size of 128MB, which is roughly 0.9-1.2GB. That is 1.5-2x larger than the TSDB target shard size. So when using the sharding calculation from TSDB, it would over-shard for data object sections, which is likely acceptable for testing and good enough for proving that local execution with the new engine works. **How does sharding with data objects in this PR work?** The query frontend passes down the calculated shards as part of the query parameters of the serialised sub-request. The logical planner on the querier stores the Shard annotation on the `MAKETABLE` alongside the stream selector. This is then used by the physical planner to filter out only the relevant sections of the resolved data objects from the metastore lookup. During exeuction, only readers for the relevant sections are initialised when performing the `DataObjScan`. Signed-off-by: Christian Haudum <christian.haudum@gmail.com> Co-authored-by: Ashwanth <iamashwanth@gmail.com>	6 months ago
Owen Diehl	ccb65f9670	feat(engine, dataobj): logql bench wiring for new engine [non-fork] (#17627) ... Signed-off-by: Christian Haudum <christian.haudum@gmail.com> Co-authored-by: Christian Haudum <christian.haudum@gmail.com> Co-authored-by: Robert Fratto <robertfratto@gmail.com>	8 months ago
Owen Diehl	920e3b23ed	chore(dataobj,testing,executor): pipeline equality testing (#17311)	8 months ago
Christian Haudum	e828c48702	chore(engine): Implement execution pipeline for the limit operator (#17264) ... Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	8 months ago